CN101685000A - Computer system and method for image boundary scan - Google Patents
Computer system and method for image boundary scan Download PDFInfo
- Publication number
- CN101685000A CN101685000A CN200810304669A CN200810304669A CN101685000A CN 101685000 A CN101685000 A CN 101685000A CN 200810304669 A CN200810304669 A CN 200810304669A CN 200810304669 A CN200810304669 A CN 200810304669A CN 101685000 A CN101685000 A CN 101685000A
- Authority
- CN
- China
- Prior art keywords
- point
- image
- scanning
- next frame
- scan
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/028—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness by measuring lateral position of a boundary of the object
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Geometry (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The present invention provides an image boundary scan method, comprising the steps of: setting scan parameters; marking the variable isS as true when a user selects the starting point Ps, the ending point Pe and the scan direction for a whole workpiece to be detected; moving the CCD lens to the current scan point Pc, intercepting the image of the workpiece to be detected, performing binary processing on the boundary of intercepted image, obtaining continuous boundary points, and focusing the image if the continuous boundary points are blurred; calculating the accurate boundary points accordingto the set scan interval when the workpiece to be detected is not scanned completely; and determining the starting point of next frame to be scanned and the position of the CCD lens, and marking isSas false. The invention also provides a computer system for image boundary scan. According to the invention, image focusing can be carried out when the image boundary points are blurred, thus improving the measured speed.
Description
Technical field
The present invention relates to a kind of image measurement system and method, relate in particular to a kind of computer system and method for image border scanning
Background technology
Measurement is the important step in the production run, and the quality of itself and product is closely bound up.For ball bar array encapsulation (BallGrid Array, BGA), the measurement of three-dimension curved surface (3D) and Transparent Parts, traditional way be adopt electric charge coupling workpiece (Charge Coupled Device, CCD) and contact measure mode.The image measuring machine that employing has CCD can also scan described BGA, 3D and workpiece, and the image that CCD is taken changes into digital document in order to being stored in the computer.
In image measuring machine measuring workpiece process, need CCD to take the image of workpiece to be scanned, then this image is carried out programmed scans.Because the CCD camera lens self characteristics requirement of image measuring machine, its workpiece image capturing range of once obtaining is limited, often the visible workpiece scope of a frame has only a monobasic coin-size, if the size that the scope of workpiece for measurement can be absorbed greater than CCD camera lens one frame picture, then need repeatedly mobile CCD camera lens, make the CCD camera lens can photograph other positions of workpiece for measurement.
, application number open on February 13rd, 2008 is 200610062038.7 Chinese patent application case, disclosed a kind of image border scanning system and method.This method comprises: the boundary scan parameter is set; When the scanning beginning, carry out the image focusing; Intercept a two field picture and this image is carried out binary conversion treatment; Seek the analyzing spot row bound scanning of going forward side by side; Multiple scanning is formed path, closed border up to current scan point and first analyzing spot.But the each scanning of this method all needs to carry out image focusing, and is to carry out binary conversion treatment at entire image during Flame Image Process, has increased calculated amount, has reduced sweep velocity.
Summary of the invention
In view of above content, be necessary to provide a kind of computer system that is used for image border scanning, it judges earlier whether the frontier point of current image is fuzzy when image border scanning, if fuzzy then carry out the image focusing automatically, and only binary conversion treatment is carried out on the border of current image during image processing.
Also be necessary to provide a kind of image border scanning method, it judges earlier whether the frontier point of current image is fuzzy when image border scanning, if fuzzy then carry out the image focusing automatically, and binary conversion treatment would be carried out on the border of current image during image processing.
A kind of computer system that is used for image border scanning, this computer system links to each other with image measuring machine, and described computer system comprises: parameter is provided with module, is used to be provided with sweep parameter, and described sweep parameter comprises the length and the sweep spacing of sweep trace; The image Focusing module is used for behind starting point Ps, the end point Pe and direction of scanning of the whole workpiece for measurement of the selected scanning of user token variable isS=true, and current scan point Pc=Ps; Described image Focusing module also is used for the CCD camera lens of image measuring machine is moved to current scan point Pc; Image processing module is used to intercept the image of workpiece for measurement, and binary conversion treatment is carried out on the border of intercepting image, obtains the continuum boundary point; Described image Focusing module is used to also judge whether described continuum boundary point is fuzzy, if fuzzy, then carries out the image focusing; The boundary scan module is used to judge whether been scanned of workpiece for measurement, if, then reading scan success; Described boundary scan module, also be used for when workpiece for measurement does not have been scanned, according to described continuum boundary point, calculate smart endpoint according to the sweep spacing that is provided with, selecting last frontier point from described smart endpoint is the starting point of next frame scanning, and the position when determining the scanning of CCD camera lens next frame according to the starting point of next frame scanning, mark isS=false, the starting point of Pc=next frame scanning, the scanning of beginning next frame.
A kind of image border scanning method is applied to comprise in the image measurement system of Test Host and image measuring machine that this method comprises the steps: that (a) is provided with sweep parameter, and described sweep parameter comprises the length and the sweep spacing of sweep trace; (b) behind starting point Ps, the end point Pe and direction of scanning of the whole workpiece for measurement of the selected scanning of user, token variable isS=true, and current scan point Pc=Ps; (c) the CCD camera lens with image measuring machine moves to current scan point Pc; (d) image of intercepting workpiece for measurement carries out binary conversion treatment to the border of intercepting image, obtains the continuum boundary point, if described continuum boundary point fuzziness then carries out the image focusing and repeats this step; (e) judge whether been scanned of workpiece for measurement, if, then reading scan success, if not, step (f) then entered; (f) according to described continuum boundary point, calculate smart endpoint according to the sweep spacing that is provided with, selecting last frontier point from described smart endpoint is the starting point of next frame scanning, and the position when determining the scanning of CCD camera lens next frame according to the starting point of this next frame scanning, mark isS=false, the starting point of Pc=next frame scanning, flow process forwards step (c) to.
Compared to prior art, the computer system of described image border scanning and method, when image border scanning, whether the frontier point of judging earlier current image is fuzzy, if it is fuzzy then carry out the image focusing automatically, and only binary conversion treatment is carried out on the border of current image during image processing, thereby reduced calculated amount, improved sweep velocity.
Description of drawings
Fig. 1 is the system architecture diagram of the computer system preferred embodiment of image border scanning of the present invention.
Fig. 2 is the synoptic diagram of image measuring machine.
Fig. 3 is the synoptic diagram that calculates sweep trace starting point and end point.
Fig. 4 is the gradient curve figure from the sweep trace starting point to end point.
Fig. 5 is that gradient is asked for synoptic diagram.
Fig. 6 is a synoptic diagram of determining the position of the starting point of next frame scanning and CCD camera lens.
Fig. 7 is the process flow diagram of image border scanning method of the present invention preferred embodiment.
Fig. 8 is that step is judged the whether particular flow sheet of been scanned of workpiece for measurement among Fig. 7.
Embodiment
As shown in Figure 1, be the system architecture diagram of the computer system preferred embodiment of image border scanning of the present invention.This computer system mainly comprises display device 1, Test Host 2 and input equipment 4.Described Test Host 2 links to each other with image measuring machine 3, and wherein, this Test Host 2 comprises memory bank 20 and boundary scan program 21.Described memory bank 20 can be the hard disk in the Test Host 2 etc., stores sweep parameter 22.Described sweep parameter 22 can be set by the user, and also can be arranged in the program to immobilize, and comprises the width of length, sweep trace of sweep trace and sweep spacing etc.
The composition of described image measuring machine 3 as shown in Figure 2, this image measuring machine 3 all is equipped with motor (not shown among Fig. 2) in X-axis, Y-axis and Z-direction, its chief component comprises board top cover 31, CCD camera lens 32, board workplace 33 and board main body 34, is placed with workpiece for measurement 35 on the described board workplace 33.Described CCD camera lens 32 is used to absorb the image of workpiece for measurement 35, and the image of picked-up is sent to Test Host 2.In CCD camera lens 32 picked-up image processes, because its coverage is fixed, when its coverage during less than workpiece for measurement 35 big or small, described boundary scan program 21 moves by control X-axis motor and Y-axis motor, and then change the position of board workplace 33 on X-axis and Y direction (X-axis in the present embodiment and Y direction are horizontal direction), make CCD camera lens 32 can photograph other positions on workpiece for measurement 35 horizontal directions.Z axle motor is used to control CCD camera lens 32 moving in vertical direction, and for example, Z axle motor can make this CCD camera lens 32 and workpiece for measurement 35 focusings by mobile CCD camera lens 32.
The CCD camera lens 32 that described boundary scan program 21 is used for controlling image measuring machine 3 moves, and the border of workpiece for measurement 35 is scanned.
Described Test Host 2 is connected with display device 1, is used to show that CCD camera lens 32 sends the image of Test Host 2 to.Described input equipment 4 can be keyboard and mouse etc., is used to carry out data input etc.
Described boundary scan program 21 comprises that parameter is provided with module 210, image Focusing module 211, image processing module 212 and boundary scan module 213.The alleged module of the present invention is to finish the computer program code segments of a specific function, is more suitable for therefore below the present invention software description all being described with module in describing the implementation of software in computing machine than program.
Described parameter is provided with module 210 and is used to be provided with sweep parameter 22, and is kept in the memory bank 20.Described sweep parameter 22 comprises the width of length, sweep trace of sweep trace and sweep spacing etc.Wherein, the length range of sweep trace is 0＜L＜80 pixel (pixel), and the width range of sweep trace is 0＜W＜100pixel.The length of sweep trace is used for determining the starting point and the end point of sweep trace, and the width of sweep trace is used for determining the density of sweep trace.
Since when the scope of workpiece for measurement 35 greater than CCD camera lens 32 1 frame pictures can absorb big or small the time, need the scanning of CCD camera lens 32 multiframes, just can finish the scanning of whole workpiece for measurement 35, therefore, behind starting point (being labeled as Ps), end point (being labeled as Pe) and the direction of scanning of the whole workpiece for measurement 35 of the selected scanning of user (clockwise or counterclockwise), described image Focusing module 211 moves to current scan point with the CCD camera lens 32 of image measuring machine 3 and (is labeled as Pc, during first frame scan, Pc and Ps overlap).When first frame scan, token variable isS=true, when not being first frame scan, token variable isS=false.
Described image processing module 212 is used to intercept the image of the workpiece for measurement 35 that CCD camera lens 32 sends, and calculate the average gray of the image that intercepts, and binary conversion treatment is carried out on the border to the intercepting image under this average gray.The calculating of described average gray is meant the gray level sum of all pixels in the image number divided by pixel.Those skilled in the art generally is defined as 255 with the gray-scale value of white, the black gray value defined is 0, and be divided into 256 grades equably by black shading value in vain, image processing module 212 is the cut off value of black and white conversion with the average gray value that is calculated, and described intercepting image is divided into black, white two kinds of colors.Described cut off value can be specified by the user, also can be calculated automatically according to image brilliance by image processing module 212.
Wherein, the image binaryzation is meant that the image with a plurality of gray levels is converted into the image that has only two gray levels (0 and 255), so that the identification of the outstanding and image of feature.The binary conversion treatment of image boundary is meant the border of binaryzation image.
Described image processing module 212 also is used for obtaining the continuum boundary point on the image boundary after the binary conversion treatment, described continuum boundary point is that unit is arranged with the pixel.Particularly, if current scan point Pc is a frontier point, then image processing module 212 obtains near the frontier point of this frontier point, utilizes recurrence method to continue other frontier point of search then; If Pc is not a frontier point, then image processing module 212 is sought the nearest frontier point of distance P c according to clockwise direction or counter clockwise direction, utilizes recurrence method to continue other frontier point of search then.
Described image Focusing module 211 is used to also judge whether described continuum boundary point is fuzzy, if fuzzy, then carries out the image focusing.Wherein, judging that described continuum boundary point is whether fuzzy comprises: the frontier point of the some of taking a sample from described continuum boundary point, calculate the average gradient value of this sampling frontier point, the average gradient value of frontier point was less than the threshold values of setting if should take a sample, then judge described continuum boundary point fuzziness, otherwise, judge that described continuum boundary point is clear.
Described boundary scan module 213 is used to judge whether been scanned of described workpiece for measurement 35.Particularly, consult shown in Figure 8, boundary scan module 213 judges earlier that Pe is whether in described continuum boundary point, if, then judge workpiece for measurement 35 been scanned, otherwise, continue to judge whether isS=false and Ps in described continuum boundary point, if, then judge workpiece for measurement 35 been scanned, otherwise, judge whether that further isS=true and described continuum boundary point join end to end, if, then judge workpiece for measurement 35 been scanned, otherwise, judge that workpiece for measurement 35 does not have been scanned, the scanning of beginning next frame.If described workpiece for measurement 35 been scanned, then boundary scan module 213 reading scans success for example, is ejected a dialog box, reading scan end etc. on display device 1.Wherein, whether end to end algorithm is as shown in table 1 to judge described continuum boundary point:
Table 1
P1 represents first point of continuum boundary point, if last of continuum boundary point any one position o'clock in 1～8 judges that then described continuum boundary point joins end to end.
Described boundary scan module 213 also is used for when described workpiece for measurement 35 does not have been scanned, according to described continuum boundary point, calculates smart endpoint according to the sweep spacing that is provided with.Before calculating smart endpoint, need calculate the starting point and the end point of sweep trace.
Particularly, boundary scan module 213 is earlier according to the sweep spacing that is provided with, from described continuum boundary point, take a sample, calculate the tangent line vector sum normal line vector of sampling frontier point, calculate the starting point and the end point of described sweep trace respectively according to the length of this normal line vector and sweep trace, then, on the image boundary after the binary conversion treatment, seek smart endpoint according to this starting point and end point.
As shown in Figure 3, be the synoptic diagram that calculates sweep trace starting point and end point.The P point is represented current scan point, the tangent line vector that P is ordered can and neighbouringly obtain (first kind of algorithm) by least square fitting by the P point, also can obtain (second kind of algorithm), adopt second kind of algorithm in the present embodiment by asking through the straight line between preceding n the point of P point and n the point in P point back.As shown in Figure 3, the P1 point is preceding the 3rd point of P point, and the P2 point is the 3rd point in P point back, connects P1 point and P2 point and is the tangent line vector T that P is ordered, and the normal line vector N that P is ordered is perpendicular to T and pass through the P point, and the starting point S of sweep trace and end point E are positioned on the normal line vector N that P orders.The vector of unit length of supposing the tangent line vector T for i, j}, then the vector of unit length of normal line vector N be j, i} can calculate the coordinate of sweep trace starting point S and end point E according to following formula:
Sx＝Px-(j)*L1，Sy＝Py-i*L1
Ex＝Px+(j)*L2，Ey＝Py+i*L2
Wherein, Px represents the X-axis coordinate of current scan point P, and Py represents the Y-axis coordinate of current scan point P, Sx represents the X-axis coordinate of sweep trace starting point S, Sy represents the Y-axis coordinate of sweep trace starting point S, and Ex represents the X-axis coordinate of sweep trace end point E, and Ey represents the Y-axis coordinate of sweep trace end point E.The size that L1 adds L2 equals the length of described sweep trace, in the present embodiment, and L1=L2.
Described boundary scan module 213 is obtained the gradient curve figure from sweep trace starting point S to end point E behind the coordinate of obtaining described sweep trace starting point S and end point E, the summit of getting this gradient curve figure then promptly obtains smart endpoint.As shown in Figure 4, be gradient curve figure from the sweep trace starting point to end point, the smart endpoint that the h point is promptly obtained.Wherein, the gradient acquiring method of frontier point as shown in Figure 5.
Described boundary scan module 213 also is used for selecting the starting point of last frontier point as next frame scanning from described smart endpoint, and the position when determining the scanning of CCD camera lens 32 next frames according to the starting point of this next frame scanning, then, mark isS=false, the starting point of Pc=next frame scanning.Wherein, determine that the principle of CCD camera lens 32 next frames when scanning position is: the imagery zone of this CCD camera lens 32 is centered close on the tangent line of starting point of next frame scanning, and the starting point of this next frame scanning is in the image scan zone.Described image scan zone is the subregion of described imagery zone.As shown in Figure 6, be the synoptic diagram of determining the position of the starting point of next frame scanning and CCD camera lens 32.Wherein, I represents imagery zone, S represents the image scan zone, Pc1 represents current scan point, Pm1 represents the position of current C CD camera lens 32, and Pe1 represents last smart endpoint in the current scanning, i.e. the starting point (being labeled as Pc2) of next frame scanning, the position of the CCD camera lens 32 when Pm2 represents next frame scanning, last smart endpoint when Pe2 represents next frame scanning.
In other embodiments, for the purpose of more accurate, described boundary scan module 213 also is used for when scanning successfully, according to described continuum boundary point, calculates the smart endpoint of each frontier point that is scanned according to the sweep spacing that is provided with.
As shown in Figure 7, be the process flow diagram of image border scanning method of the present invention preferred embodiment.Step S40 is provided with module 210 by described parameter sweep parameter 22 is set, and is kept in the memory bank 20.Described sweep parameter 22 comprises the width of length, sweep trace of sweep trace and sweep spacing etc.Wherein, the length range of sweep trace is 0＜L＜80 pixel (pixel), and the width range of sweep trace is 0＜W＜100pixel.The length of sweep trace is used for determining the starting point and the end point of sweep trace, and the width of sweep trace is used for determining the density of sweep trace.
Step S41, behind starting point (being labeled as Ps), end point (being labeled as Pe) and the direction of scanning of the whole workpiece for measurement 35 of the selected scanning of user, described image Focusing module 211 token variable isS=true.Described direction of scanning comprises clockwise and is counterclockwise.Described variable i sS is used to mark whether first frame scan, and promptly if first frame scan, isS=true is if not first frame scan, isS=false.
Step S42, described image Focusing module 211 moves to current scan point (be labeled as Pc, during first frame scan, Pc and Ps overlap) with the CCD camera lens 32 of image measuring machine 3.
Step S43, the image of the workpiece for measurement 35 that described image processing module 212 intercepting CCD camera lenses 32 send, calculate the average gray of the image that intercepts, and binary conversion treatment is carried out on the border to the intercepting image under this average gray, then, obtain the continuum boundary point on the image boundary after the binary conversion treatment, described continuum boundary point is that unit is arranged with the pixel.
Step S44, described image Focusing module 211 judge whether described continuum boundary point is fuzzy, if fuzzy, execution in step S45, otherwise, execution in step S46.Wherein, judging that described continuum boundary point is whether fuzzy comprises: the frontier point of getting some from described continuum boundary point, calculate the average gradient value of this sampling frontier point, the average gradient value of frontier point was less than the threshold values of setting if should take a sample, then judge described continuum boundary point fuzziness, otherwise, judge that described continuum boundary point is clear.
Step S45, described image Focusing module 211 carry out the image focusing, then, and execution in step S43.
Step S46, described boundary scan module 213 is judged whether been scanned of described workpiece for measurement 35, if, execution in step S49, otherwise, execution in step S47.
Step S47, described boundary scan module 213 calculates smart endpoint according to described continuum boundary point according to the sweep spacing that is provided with.Before calculating smart endpoint, need calculate the starting point and the end point of sweep trace.
Particularly, boundary scan module 213 is earlier according to the sweep spacing that is provided with, from described continuum boundary point, take a sample, calculate the tangent line vector sum normal line vector of sampling frontier point, calculate the starting point and the end point of described sweep trace according to the length of this normal line vector and sweep trace respectively.Wherein, the calculating of the starting point of sweep trace and end point as shown in Figure 3.Then, described boundary scan module 213 is sought accurate frontier point according to the starting point and the end point of described sweep trace on the image boundary after the binary conversion treatment.Be that described boundary scan module 213 is obtained the gradient curve figure from the sweep trace starting point to end point earlier, the summit of getting this gradient curve figure then promptly gets accurate frontier point.As shown in Figure 4, be gradient curve figure from the sweep trace starting point to end point, the smart endpoint that the h point is promptly obtained.Wherein, the gradient acquiring method of frontier point as shown in Figure 5.
Step S48, described boundary scan module 213 is selected the starting point of last frontier point as next frame scanning from described smart endpoint, and the position when determining the scanning of CCD camera lens 32 next frames according to the starting point of this next frame scanning, then, mark isS=false, the starting point of Pc=next frame scanning, flow process forwards step S42 to.Wherein, determine that the principle of CCD camera lens 32 next frames when scanning position is: the imagery zone of this CCD camera lens 32 is centered close on the tangent line of starting point of next frame scanning, and the starting point of this next frame scanning is in the image scan zone.Described image scan zone is the subregion of described imagery zone.Wherein, the position of determining the starting point of next frame scanning and CCD camera lens 32 as shown in Figure 6.
Step S49, boundary scan module 213 reading scans successes for example, is ejected a dialog box, reading scan end etc. on display device 1.
In other embodiments, for the purpose of more accurate, described boundary scan module 213 can also calculate the smart endpoint of each frontier point that is scanned according to described continuum boundary point according to the sweep spacing that is provided with.
As shown in Figure 8, be that step S46 judges the whether particular flow sheet of been scanned of workpiece for measurement among Fig. 7.Step S461, boundary scan module 213 is judged Pe whether in described continuum boundary point, if, execution in step S465, otherwise, execution in step S462.
Step S462, boundary scan module 213 judges whether isS=false and Ps in described continuum boundary point, if, execution in step S465, otherwise, execution in step S463.
Step S463, boundary scan module 213 judges whether that isS=true and described continuum boundary point join end to end, if, execution in step S465, otherwise, execution in step S464.
Step S464, boundary scan module 213 judges that workpiece for measurement 35 does not have been scanned, the scanning of beginning next frame, flow process forwards step S47 to.
Step S465, boundary scan module 213 is judged workpiece for measurement 35 been scanned, flow process forwards step S49 to.
It should be noted that at last, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement technical scheme of the present invention, and not break away from the spirit and scope of technical solution of the present invention.
Claims (10)
1. an image border scanning method is applied to comprise in the image measurement system of Test Host and image measuring machine, and it is characterized in that, this method comprises the steps:
(a) sweep parameter is set, described sweep parameter comprises the length and the sweep spacing of sweep trace;
(b) behind starting point Ps, the end point Pe and direction of scanning of the whole workpiece for measurement of the selected scanning of user, token variable isS=true, and current scan point Pc=Ps;
(c) the CCD camera lens with image measuring machine moves to current scan point Pc;
(d) image of intercepting workpiece for measurement carries out binary conversion treatment to the border of intercepting image, obtains the continuum boundary point, if described continuum boundary point fuzziness then carries out the image focusing and repeats this step;
(e) judge whether been scanned of workpiece for measurement, if, then reading scan success, if not, step (f) then entered; And
(f) according to described continuum boundary point, calculate smart endpoint according to the sweep spacing that is provided with, selecting last frontier point from described smart endpoint is the starting point of next frame scanning, and the position when determining the scanning of CCD camera lens next frame according to the starting point of this next frame scanning, mark isS=false, the starting point of Pc=next frame scanning, flow process forwards step (c) to.
2. image border scanning method as claimed in claim 1, it is characterized in that, step is judged that described continuum boundary point is whether fuzzy and is comprised: the frontier point of the some of taking a sample from described continuum boundary point, calculate the average gradient value of this sampling frontier point, the average gradient value of frontier point was less than the threshold values of setting if should take a sample, then judge described continuum boundary point fuzziness, otherwise, judge that described continuum boundary point is clear.
3. image border scanning method as claimed in claim 1 is characterized in that, judges whether been scanned comprises workpiece for measurement in the described step (e):
(e1) judge Pe whether in described continuum boundary point, if, execution in step (e5), otherwise, execution in step (e2);
(e2) judge whether isS=false and Ps in described continuum boundary point, if, execution in step (e5), otherwise, execution in step (e3);
(e3) judge whether that isS=true and described continuum boundary point join end to end, if, execution in step (e5), otherwise, execution in step (e4);
(e4) judge that workpiece for measurement does not have been scanned, enter step (f);
(e5) judge the workpiece for measurement been scanned.
4. image border scanning method as claimed in claim 1 is characterized in that, described step calculates accurate frontier point according to the sweep spacing that is provided with and comprises according to described continuum boundary point:
According to the sweep spacing that is provided with, from described continuum boundary point, take a sample, calculate the normal line vector of sampling frontier point, calculate the starting point and the end point of described sweep trace respectively according to the length of this normal line vector and sweep trace; And
Obtain the gradient curve figure from the sweep trace starting point to end point, the summit of getting this gradient curve figure then promptly obtains smart endpoint.
5. image border scanning method as claimed in claim 1, it is characterized in that, the principle of determining CCD camera lens next frame when scanning position is: the imagery zone of this CCD camera lens is centered close on the tangent line of starting point of next frame scanning, and the starting point of this next frame scanning is in the image scan zone.
6. computer system that is used for image border scanning, this computer system links to each other with image measuring machine, it is characterized in that, and described computer system comprises:
Parameter is provided with module, is used to be provided with sweep parameter, and described sweep parameter comprises the length and the sweep spacing of sweep trace;
The image Focusing module is used for behind starting point Ps, the end point Pe and direction of scanning of the whole workpiece for measurement of the selected scanning of user token variable isS=true, and current scan point Pc=Ps;
Described image Focusing module also is used for the CCD camera lens of image measuring machine is moved to current scan point Pc;
Image processing module is used to intercept the image of workpiece for measurement, and binary conversion treatment is carried out on the border of intercepting image, obtains the continuum boundary point;
Described image Focusing module is used to also judge whether described continuum boundary point is fuzzy, if fuzzy, then carries out the image focusing;
The boundary scan module is used to judge whether been scanned of workpiece for measurement, if, then reading scan success; And
Described boundary scan module, also be used for when workpiece for measurement does not have been scanned, according to described continuum boundary point, calculate smart endpoint according to the sweep spacing that is provided with, selecting last frontier point from described smart endpoint is the starting point of next frame scanning, and the position when determining the scanning of CCD camera lens next frame according to the starting point of next frame scanning, mark isS=false, the starting point of Pc=next frame scanning, the scanning of beginning next frame.
7. the computer system of image border scanning as claimed in claim 6, it is characterized in that, described image Focusing module is judged that described continuum boundary point is whether fuzzy and is comprised: the frontier point of the some of taking a sample from described continuum boundary point, calculate the average gradient value of this sampling frontier point, the average gradient value of frontier point was less than the threshold values of setting if should take a sample, then judge described continuum boundary point fuzziness, otherwise, judge that described continuum boundary point is clear.
8. the computer system of image border scanning as claimed in claim 6 is characterized in that, described image processing module obtains the continuum boundary point and comprises:
If current scan point Pc is a frontier point, then image processing module obtains near the frontier point of this frontier point, utilizes recurrence method to continue other frontier point of search then; And
If current scan point Pc is not a frontier point, then image processing module is sought the frontier point nearest apart from current scan point Pc according to clockwise direction or counter clockwise direction, utilizes recurrence method to continue other frontier point of search then.
9. the computer system of image border scanning as claimed in claim 6 is characterized in that, described boundary scan module calculates smart endpoint according to the sweep spacing that is provided with and comprises according to described continuum boundary point:
According to the sweep spacing that is provided with, from described continuum boundary point, take a sample, calculate the normal line vector of sampling frontier point, calculate the starting point and the end point of described sweep trace respectively according to the length of this normal line vector and sweep trace; And
Obtain the gradient curve figure from the sweep trace starting point to end point, the summit of getting this gradient curve figure then promptly obtains smart endpoint.
10. the computer system of image border scanning as claimed in claim 6, it is characterized in that, described boundary scan module determines that the principle of CCD camera lens next frame when scanning position is: the imagery zone of this CCD camera lens is centered close on the tangent line of starting point of next frame scanning, and the starting point of this next frame scanning is in the image scan zone.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008103046694A CN101685000B (en) | 2008-09-25 | 2008-09-25 | Computer system and method for image boundary scan |
| US12/430,782 US8274597B2 (en) | 2008-09-25 | 2009-04-27 | System and method for measuring a border of an image of an object |
| US13/587,874 US8390731B2 (en) | 2008-09-25 | 2012-08-16 | System and method for measuring a border of an image of an object |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008103046694A CN101685000B (en) | 2008-09-25 | 2008-09-25 | Computer system and method for image boundary scan |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101685000A true CN101685000A (en) | 2010-03-31 |
| CN101685000B CN101685000B (en) | 2012-05-30 |
Family
ID=42037261
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2008103046694A Expired - Fee Related CN101685000B (en) | 2008-09-25 | 2008-09-25 | Computer system and method for image boundary scan |
Country Status (2)
| Country | Link |
|---|---|
| US (2) | US8274597B2 (en) |
| CN (1) | CN101685000B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102425989A (en) * | 2011-08-22 | 2012-04-25 | 天津大学 | Image detection-based two-dimensional characteristic size measurement method |
| US12014557B2 (en) | 2021-12-02 | 2024-06-18 | V5Med Inc. | High-speed automatic scanning system for interpreting images with AI assistance and method using the same |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102759788B (en) * | 2011-04-26 | 2015-10-14 | 鸿富锦精密工业（深圳）有限公司 | Surface multi-spot system and method |
| CN102752511B (en) * | 2012-07-09 | 2016-07-27 | 宁波江丰生物信息技术有限公司 | The acquisition methods of linear array scanning system focus, device and linear array scanning system |
| JP6221656B2 (en) * | 2013-11-08 | 2017-11-01 | 株式会社リコー | Information processing apparatus, information processing method, and program |
| CN113865488B (en) * | 2021-09-24 | 2023-10-27 | 北京京东方技术开发有限公司 | Distance measuring method, electronic equipment and computer readable storage medium |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5608816A (en) * | 1993-12-24 | 1997-03-04 | Matsushita Electric Industrial Co., Ltd. | Apparatus for inspecting a wiring pattern according to a micro-inspection and a macro-inspection performed in parallel |
| EP0774730B1 (en) * | 1995-11-01 | 2005-08-24 | Canon Kabushiki Kaisha | Object extraction method, and image sensing apparatus using the method |
| JP4506308B2 (en) * | 2004-07-02 | 2010-07-21 | 三菱電機株式会社 | Image processing apparatus and image monitoring system using the image processing apparatus |
| US7751622B2 (en) * | 2005-08-22 | 2010-07-06 | Carestream Health, Inc. | Method and system for detection of undesirable images |
| CN101122457B (en) * | 2006-08-09 | 2010-09-29 | 鸿富锦精密工业（深圳）有限公司 | Image border scanning system and method |
| CN101469984B (en) * | 2007-12-24 | 2010-09-29 | 鸿富锦精密工业（深圳）有限公司 | Image impurity analysis system and method |
| CN101952854B (en) * | 2008-04-21 | 2012-10-24 | 夏普株式会社 | Image processing device, display, image processing method, program, and recording medium |
| US8073246B2 (en) * | 2008-11-07 | 2011-12-06 | Omnivision Technologies, Inc. | Modifying color and panchromatic channel CFA image |
-
2008
- 2008-09-25 CN CN2008103046694A patent/CN101685000B/en not_active Expired - Fee Related
-
2009
- 2009-04-27 US US12/430,782 patent/US8274597B2/en not_active Expired - Fee Related
-
2012
- 2012-08-16 US US13/587,874 patent/US8390731B2/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102425989A (en) * | 2011-08-22 | 2012-04-25 | 天津大学 | Image detection-based two-dimensional characteristic size measurement method |
| US12014557B2 (en) | 2021-12-02 | 2024-06-18 | V5Med Inc. | High-speed automatic scanning system for interpreting images with AI assistance and method using the same |
Also Published As
| Publication number | Publication date |
|---|---|
| US8390731B2 (en) | 2013-03-05 |
| US20120308158A1 (en) | 2012-12-06 |
| US8274597B2 (en) | 2012-09-25 |
| CN101685000B (en) | 2012-05-30 |
| US20100073550A1 (en) | 2010-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109341527B (en) | Automatic shadow compensation structured light projection three-dimensional measurement system and method | |
| US7630539B2 (en) | Image processing apparatus | |
| CN102103753B (en) | Use method and the terminal of real time camera estimation detect and track Moving Objects | |
| CN101685000B (en) | Computer system and method for image boundary scan | |
| TWI419081B (en) | Method and system for providing augmented reality based on marker tracing, and computer program product thereof | |
| CN101122457B (en) | Image border scanning system and method | |
| CN109472271B (en) | Printed circuit board image contour extraction method and device | |
| JP6899189B2 (en) | Systems and methods for efficiently scoring probes in images with a vision system | |
| JP4416039B2 (en) | Striped pattern detection system, striped pattern detection method, and striped pattern detection program | |
| CN109345597B (en) | Camera calibration image acquisition method and device based on augmented reality | |
| US8315457B2 (en) | System and method for performing multi-image training for pattern recognition and registration | |
| CN104103069B (en) | Image processing apparatus, image processing method and recording medium | |
| CN104376573A (en) | Image spot detecting method and system | |
| CN113340909A (en) | Glue line defect detection method based on machine vision | |
| KR101653861B1 (en) | Drawing data generating method, drawing method, drawing data generating apparatus and drawing apparatus | |
| CN115546016B (en) | Method for acquiring and processing 2D (two-dimensional) and 3D (three-dimensional) images of PCB (printed Circuit Board) and related device | |
| TWI450572B (en) | Computing system and method for scanning a boundary of an image of an object | |
| CN116703803A (en) | Method, device and system for detecting burrs at edges of battery pole pieces | |
| CN113921412A (en) | Method, device and equipment for calculating chip period in wafer | |
| CN109977740B (en) | Depth map-based hand tracking method | |
| TWI543589B (en) | Image Processing Method for an Original Mosaic | |
| JP2710685B2 (en) | Defect detection method by visual inspection | |
| CN117036364B (en) | Image processing method and device, storage medium and computing equipment | |
| CN116580277B (en) | Deep learning-based bottom electronic identification tag missing image identification method | |
| CN117541563A (en) | Image defect detection method, device, computer equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120530 Termination date: 20170925 |